Leveraging Advanced Statistical Methods in Empirical Educational Research: Handling Missing Data and Harnessing Machine Learning Methods
Using tree-based imputation methods in comparison to MICE for longitudinal and multilevel data
Jakob Schwerter, Ketevan Gurtskaia, Andres Romero, Birgit Zeyer-Gliozzo, Philipp Doebler
Resampling-Based Approaches for Nonparametric MANOVA in the Presence of Missing Data
Lubna Amro, Markus Pauly
Prediction Rule Ensembles: Introduction and Application with Multiple Imputation
Philipp Doebler, Marjolein Fokkema, Vincent Schroeder, Jakob Schwerter
A Pilot Study on the Use of Transformer Models to Evaluate Open-Ended Response Formats in Educational Assessments
Rudolf Debelak, Benjamin Wolf
Folien auf github verfügbar unter
Using tree-based imputation methods in comparison to MICE for longitudinal and multilevel data
Prediction Rule Ensembles: Introduction and Application with Multiple Imputation
A Pilot Study on the Use of Transformer Models to Evaluate Open-Ended Response Formats in Educational Assessments
Using tree-based imputation methods in comparison to MICE for longitudinal and multilevel data
Prediction Rule Ensembles: Introduction and Application with Multiple Imputation
A Pilot Study on the Use of Transformer Models to Evaluate Open-Ended Response Formats in Educational Assessments